The correct detection of atrial arrhythmias by pacemakers is often limited by the presence of far-field R waves (FFRWs) in the atrial electrogram. Digital signal processing (DSP) of intracardiac signals is assumed to provide improved discrimination between P waves and FFRWs when compared to current methods. For this purpose, 100 bipolar and unipolar intracardiac atrial recordings from 31 patients were collected during pacemaker replacement and used for the off-line application of a novel DSP algorithm. Digital processing of the atrial intracardiac electrogram (IEGM) signals (8 bit, 800 samples/s) included filtering and calculation of the maximum amplitude and slope of the detected events. The form parameter was calculated, being the sum of the most negative value of the amplitude and that of the slope of the detected event. The algorithm collects form parameter data of P waves and FFRWs and composes histograms of these data. A sufficiently large gap between the FFRW and P wave histograms allows discrimination of these two signals based on form parameters. Three independent observers reviewed the reliability of classification with this algorithm. Sensitivity and specificity of FFRW detection were 99.63% and 100%, respectively, and no P waves were falsely classified. It can be concluded that this novel DSP algorithm shows excellent discrimination of FFRWs under off-line conditions and justify the implementation of this algorithm in future pacemakers for real-time discrimination between P waves and FFRWs. This method prevents false mode switching and allows correct and immediate intervention pacing for atrial tachyarrhythmias.

Dynamic characteristics of heart rate in response to sinusoidal variations of work load were analysed in 8 male and 3 female untrained students exercising in a sitting position on a bicycle ergometer. The mean work load was 90 watt in men and 60 watt in women, the amplitudes being 50 and 30 watt respectively. Nine different frequencies were used, the periods varying from 0.5 to 15.0 min. By means of harmonic analysis, the fundamental components in the response of the heart rate have been shown to prevail over the 2nd and 3rd harmonics, indicating a mainly linear behaviour of the control system in the work-load range studied. A comparison of the frequency response of untrained males and females observed in this study and of trained sportsmen, investigated by wigertz (1970), reveals differences between the groups. The individual and ensemble mean frequency responses have been described by several transfer functions, the best fit having been obtained with functions containing two time constants including one with a highly damped oscillating element. The dominating dynamic parameter is a time constant of about 20 to 30 sec. This time constant tends to be shorter and its portion of the frequency response diminishes in order from the untrained females and males to the trained sportsmen. The individual time constant decreases as the PWC170 increases, and is therefore a suitable criterion for estimating the physical performance of individuals under dynamic conditions.

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By improving atrial signal discrimination, morphology analysis of atrial electrograms allows for high atrial sensitivity settings, and potentially improves the reliability of atrial arrhythmia diagnostics in heart rhythm devices.

Background. Far-Field R-Wave (FFRW) oversensing and P wave blanking are the major causes of inaccurate atrial signal classification in current pacemaker (PM) devices leading to inaccurate stored diagnostic information and to inadequate PM reactions like mode-switching or preventive pacing. The prospective and multi-center MARS (Morphology of Atrial Signals) study therefore investigated during daily life the capabilities of Digital Signal Processing (DSP) in an implanted dual chamber PM to improve P-wave classification accuracy. Methods . 55 patients with an implanted dual chamber PM (Vitatron T- or C-series) were included: During 24 hours with daily life activity and a stress test, a Holter ECG collected surface ECG, PM markers and all atrial EGM’s. The DSP algorithm analysed atrial events sensed nearby a ventricular event using the minimum and the maximum amplitude of the digitalized and filtered signal and the maximum and minimum amplitude of the slope signal. After comparing to the characteristics of a normal P wave, each of these atrial signals were then classified as a true atrial signal or FFRW. DSP classification results were then compared to the conventional PM signal classification by three independent reviewers. Results . Classification accuracy for the traditional PM functionality after optimizing blanking and sensitivity settings was 97.1% (19.5–100%) as compared to 99.4% (76.9–100%) using the DSP algorithm (p<0.001). Conclusion . The DSP algorithm significantly improved the classification accuracy of sensed atrial events as an important prerequisite for a correct diagnostic and therapeutic PM function. The herewith presented approach of analysing atrial signals by form and timing may allow to reduce or even eliminate atrial blanking periods thus leading to larger PM sensing windows to prevent from atrial tachyarrhythmia undersensing without an increase in FFRW sensing.